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ŞERİATA UYGUN HİSSE SENEDİ OPTİMİZASYONU İÇIN İSLAMİ META-UYARIM PORTFÖY TEORİSİ

Year 2023, Volume: 9 Issue: 1, 23 - 36, 30.06.2023
https://doi.org/10.54863/jief.1180652

Abstract

Metaverse, son yıllarda hızlı bir gelişme yaşadı. Metaverse belirsiz bir şekilde tanımlanmıştır, ancak tipik olarak, biri metaverse içinde oynamasa bile kalıcı bir dünya ve artırılmış gerçeklik biçimleri ile karakterize edilen bir sanal gerçeklik biçimi içerir. Bu hem fiziksel hem de dijital dünyaları kapsar. Birçok şirket metaverse'i iş planlarına ve stratejilerine dahil etmiş ve müşterilerine metaverse deneyimleri sunmaktadır. Metaverse ve gelir fırsatları için önemli büyüme fırsatları göz önüne alındığında, birkaç şirket, metaverse'nin sağladığı büyüme ve kar fırsatlarını aktif olarak desteklemiştir. Bu aynı zamanda Şeriat uyumlu yatırım fonlarını bu şirketlere maruz kalma ve onlara yatırım yapma konusunda cezbetti. Fon tahsisini optimize etmek, fonlardan elde edilen getirileri maksimize etmede kritik bir unsuru temsil eder. Bu makale, Şeriata uygun hisse senedi optimizasyonu için yeni bir İslami meta-uyarım portföy teorisi sunmaktadır. Teori, metaverse şirketlerine yapılan yatırımlar için İslami gerekliliklerin bu hisseleri içeren bir portföyün performansını nasıl teşvik edebileceğini özetlemektedir. Teori, metaverse Şeriat uyumlu portföylerin performansının uyarılması için derin bir öğrenme optimizasyon çerçevesini bütünleştirir. Teori, diğerlerine kıyasla Şeriat uyumlu metaverse şirketlerinin deneyimlediği performans gelişimini gösteren, NYSE ve NASDAQ'da listelenen büyük şirketlerin bir veri setinde özetlenmiştir.

References

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  • Björk, T., Murgoci, A., & Zhou, X. Y. (2014). Mean-variance portfolio optimization with state‐dependent risk aversion. Mathematical Finance: An International Journal of Mathematics, Statistics and Financial Economics, 1-24.
  • Burggraf, T. (2021). Beyond risk parity–A machine learning-based hierarchical risk parity approach on cryptocurrencies. Finance Research Letters, 101523. Cai, X., Teo, K. L., Yang, X., & Zhou, X. Y. (2000). Portfolio optimization under a minimax rule. Management Science, 957-972.
  • Chekhlov, A., Uryasev, S., & Zabarankin, M. (2005). Drawdown measure in portfolio optimization. International Journal of Theoretical and Applied Finance, 13-58.
  • Hasan, R., Hassan, M. K., & Aliyu, S. (2020). Fintech and Islamic finance: literature review and research agenda. International Journal of Islamic Economics and Finance, 75-94.
  • Katterbauer, K., & Moschetta, P. (2022). A deep learning approach to risk management modeling for Islamic microfinance. European Journal of Islamic Finance, 35-43.
  • Katterbauer, K., Syed, H., Cleenewerck, L., & Genc, S. Y. (2022). Robo-Sukuk pricing for Chinese equities. Borsa Istanbul Review.
  • Krokhmal, P., Palmquist, J., & Uryasev, S. (2002). Portfolio optimization with conditional value-at-risk objective and constraints. Journal of risk, 43-68.
  • Markowitz, H., Todd, P., Xu, G., & Yamane, Y. (1993). Computation of mean-semivariance efficient sets by the critical line algorithm. Annals of Operations Research, 307-317.
  • Martins-Filho, C., Yao, F., & Torero, M. (2018). Nonparametric estimation of conditional value-at-risk and expected shortfall based on extreme value theory. Econometric Theory, 23-67.
  • Narin, N. G. (2021). A Content Analysis of the Metaverse Articles. Journal of Metaverse , 17-24.
  • Park, S.-M., & Kim, Y.-G. (2022). A Metaverse: taxonomy, components, applications, and open challenges. IEEE Access.
  • S&P Global. (2022). Dow Jones Islamic Market Indices Methodology. New York: S&P Dow Jones Indices.
  • Taghdiri, A. (2020). Assessing the Compatibility of Cryptocurrencies and Islamic Law. Intell. Prop. & Tech. LJ, 63.
  • Vidal-Tomás, D. (2022). The new crypto niche: NFTs, play-to-earn, and metaverse tokens. Finance Research Letters, 102742.
  • Wilson, K. B., Karg, A., & Ghaderi, H. (2021). . Prospecting non-fungible tokens in the digital economy: Stakeholders and ecosystem, risk and opportunity. Business Horizons.
  • Wohlgenannt, I., Simons, A., & Stieglitz, S. (2020). Virtual reality. Business & Information Systems Engineering, 455-461.
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ISLAMIC META-STIMULATION PORTFOLIO THEORY FOR SHARIAH-COMPLIANT EQUITY OPTIMIZATION

Year 2023, Volume: 9 Issue: 1, 23 - 36, 30.06.2023
https://doi.org/10.54863/jief.1180652

Abstract

The metaverse has experienced rapid development in the last decades. The metaverse is vaguely defined, but typically includes a form of virtual reality, that is characterized by a persistent world even if one is not playing within the metaverse, and forms of augmented reality. This encompasses both the physical and digital worlds. Many companies have incorporated the metaverse in their business plan and strategies and provide metaverse experiences to their customers. Given the significant growth opportunities for the metaverse and revenue opportunities, several corporations have actively promoted the growth and profit opportunities the metaverse provides. This has also attracted Shariah-compliant investment funds to gain exposure to these corporations and invest in them. Optimizing the allocation of funds represents a critical element in maximizing returns from the funds. This paper presents a new Islamic meta-stimulation portfolio theory for Shariah-compliant equity optimization. The theory outlines how Islamic requirements for investments into metaverse companies may stimulate the performance of a portfolio containing these shares. The theory integrates a deep learning optimization framework for the stimulation of the performance of metaverse Shariah-compliant portfolios. The theory is outlined on a dataset of major NYSE and NASDAQ listed enterprises demonstrating the performance improvement experienced by Shariah-compliant metaverse corporations as compared to others.

References

  • Ahmadi-Javid, A., & Fallah-Tafti, M. (2019). Portfolio optimization with entropic value-at-risk. European Journal of Operational Research, 225-241.
  • Björk, T., Murgoci, A., & Zhou, X. Y. (2014). Mean-variance portfolio optimization with state‐dependent risk aversion. Mathematical Finance: An International Journal of Mathematics, Statistics and Financial Economics, 1-24.
  • Burggraf, T. (2021). Beyond risk parity–A machine learning-based hierarchical risk parity approach on cryptocurrencies. Finance Research Letters, 101523. Cai, X., Teo, K. L., Yang, X., & Zhou, X. Y. (2000). Portfolio optimization under a minimax rule. Management Science, 957-972.
  • Chekhlov, A., Uryasev, S., & Zabarankin, M. (2005). Drawdown measure in portfolio optimization. International Journal of Theoretical and Applied Finance, 13-58.
  • Hasan, R., Hassan, M. K., & Aliyu, S. (2020). Fintech and Islamic finance: literature review and research agenda. International Journal of Islamic Economics and Finance, 75-94.
  • Katterbauer, K., & Moschetta, P. (2022). A deep learning approach to risk management modeling for Islamic microfinance. European Journal of Islamic Finance, 35-43.
  • Katterbauer, K., Syed, H., Cleenewerck, L., & Genc, S. Y. (2022). Robo-Sukuk pricing for Chinese equities. Borsa Istanbul Review.
  • Krokhmal, P., Palmquist, J., & Uryasev, S. (2002). Portfolio optimization with conditional value-at-risk objective and constraints. Journal of risk, 43-68.
  • Markowitz, H., Todd, P., Xu, G., & Yamane, Y. (1993). Computation of mean-semivariance efficient sets by the critical line algorithm. Annals of Operations Research, 307-317.
  • Martins-Filho, C., Yao, F., & Torero, M. (2018). Nonparametric estimation of conditional value-at-risk and expected shortfall based on extreme value theory. Econometric Theory, 23-67.
  • Narin, N. G. (2021). A Content Analysis of the Metaverse Articles. Journal of Metaverse , 17-24.
  • Park, S.-M., & Kim, Y.-G. (2022). A Metaverse: taxonomy, components, applications, and open challenges. IEEE Access.
  • S&P Global. (2022). Dow Jones Islamic Market Indices Methodology. New York: S&P Dow Jones Indices.
  • Taghdiri, A. (2020). Assessing the Compatibility of Cryptocurrencies and Islamic Law. Intell. Prop. & Tech. LJ, 63.
  • Vidal-Tomás, D. (2022). The new crypto niche: NFTs, play-to-earn, and metaverse tokens. Finance Research Letters, 102742.
  • Wilson, K. B., Karg, A., & Ghaderi, H. (2021). . Prospecting non-fungible tokens in the digital economy: Stakeholders and ecosystem, risk and opportunity. Business Horizons.
  • Wohlgenannt, I., Simons, A., & Stieglitz, S. (2020). Virtual reality. Business & Information Systems Engineering, 455-461.
  • Yang, Q., Zhao, Y., Huang, H., Xiong, Z., Kang, J., & Zheng, Z. (2022). Fusing blockchain and AI with metaverse: A survey. IEEE Open Journal of the Computer Society, 122-136.
There are 18 citations in total.

Details

Primary Language English
Subjects Economics, Islamic Economy
Journal Section Articles
Authors

Klemens Katterbauer 0000-0001-5513-4418

Hassan Syed 0000-0001-9561-0810

Laurent Cleenewerck 0000-0002-9267-0428

Early Pub Date July 24, 2023
Publication Date June 30, 2023
Submission Date September 27, 2022
Acceptance Date January 14, 2023
Published in Issue Year 2023 Volume: 9 Issue: 1

Cite

APA Katterbauer, K., Syed, H., & Cleenewerck, L. (2023). ISLAMIC META-STIMULATION PORTFOLIO THEORY FOR SHARIAH-COMPLIANT EQUITY OPTIMIZATION. İslam Ekonomisi Ve Finansı Dergisi (İEFD), 9(1), 23-36. https://doi.org/10.54863/jief.1180652

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